scholarly journals Content-based image retrieval approach for biometric security using colour, texture and shape features controlled by fuzzy heuristics

2012 ◽  
Vol 78 (4) ◽  
pp. 1258-1277 ◽  
Author(s):  
Kashif Iqbal ◽  
Michael O. Odetayo ◽  
Anne James
Keyword(s):  
Image Retrieval ◽  
Content Based Image Retrieval ◽  
Shape Features ◽  
Biometric Security ◽  
Fuzzy Heuristics

Content-Based Image Retrieval Using Color, Texture and Shape Features

2016 ◽  
Vol 685 ◽  
pp. 872-876 ◽  
Author(s):  
Alexey Ponomarev ◽  
Hitesh S. Nalamwar ◽  
Ilya Babakov ◽  
Chandrakant S. Parkhi ◽  
Gaurav Buddhawar
Keyword(s):  
Image Retrieval ◽  
Digital Imaging ◽  
Imaging Techniques ◽  
Content Based Image Retrieval ◽  
Shape Features ◽  
Large Databases ◽  
The Given ◽  
Color Texture

Nowadays CBIR is getting more and more attention from organizations and researchers due to advances in digital imaging techniques. A lot of interest is getting paid to search images from large databases, as it is not only difficult and time-consuming task but sometimes frustrating for the users. This paper proposes the CBIR system based on color, texture and shape features. The proposed method employs the use of DCT and DWT along with Hierarchical k-means algorithm for faster retrieval of images. The efficiency of the given method is demonstrated by the results in the paper.

Image Recognition Based on Shape and Texture Features

2014 ◽  
Vol 536-537 ◽  
pp. 127-130
Author(s):  
Kun Geng
Keyword(s):  
Feature Extraction ◽  
Image Retrieval ◽  
Retrieval System ◽  
Texture Features ◽  
Morphological Processing ◽  
Content Based Image Retrieval ◽  
Shape Features ◽  
Key Technologies ◽  
Image Retrieval System ◽  
Important Position

Based on the shape of the image retrieval occupy an important position in the content-based image retrieval, and studied architecture, content-based image retrieval system, ie research-based image retrieval key technologies shape features for image noise in addition to the morphological processing; image segmentation; shape-based feature extraction and regional boundaries and description techniques and similarity measure techniques. The results show that the algorithm can effectively identify the characteristics of the image.

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